code: def _dist_init(rank, world_size, tempfile_name, backend):
      url = "file://" + tempfile_name
      dist.init_process_group(
          init_method=url,
          backend=backend,
          rank=rank,
          world_size=world_size,
      )
      torch.cuda.set_device(rank)
  
file_path: fairscale/tests/optim/test_oss_adascale.py
imports: from statistics import mean
  import tempfile
  import numpy
  import pytest
  import torch
  from torch import Tensor
  import torch.distributed
  import torch.multiprocessing
  from torch.nn import Linear, Sequential
  from torch.nn.parallel import DistributedDataParallel
  from torch.optim import SGD
  from fairscale.fair_dev.testing.golden_testing_data import adascale_test_data
  from fairscale.fair_dev.testing.testing import skip_if_single_gpu
  from fairscale.optim import OSS, AdaScale, AdaScaleWrapper
label_desc: Use image node_id 1 for calling a global function with example usage: _dist_init(rank, world_size, tempfile_name, backend) without return types